An Adaptive Hybrid Localization Algorithm for Wireless Sensor Network

Liu, Lijun; Wei, Yuankun; Xiu, Guoyi

doi:10.1109/imccc.2012.368

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…The core concept of RSS techniques is to utilize Radio Frequency (RF) signal propagation models, which can be derived from theoretical, hypothetical, or empirical sources, to analyze RSS data and estimate distances without requiring additional ranging hardware. These systems are not only economical but also straightforward to implement, as the majority of RF IC-chips used in wireless sensor network devices can directly furnish RSS data [7][8].…”

Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%

Enhancing Location Accuracy by Minimizing RMS Using RSS-AMLE in WSN

T P

2024

J. Infor. Electr. Electron. Eng.

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Over the past decade, there has been significant growth in wireless sensor networks, particularly in the context of industrial applications. Mobile sensor networks have garnered research interest due to their ability to facilitate communication between various devices. Still, the mobility of these nodes gives rise to challenges such as network coverage and connectivity issues. Addressing these challenges necessitates accurate estimation of sensor node locations, a critical factor in network performance. Numerous methods, such as Angle of Arrival (AOA) and Time of Arrival (TOA), have been proposed for node localization. Still, these methods are plagued by localization errors and high implementation costs. To overcome these localization errors in wireless sensor networks, we present an adaptive approach based on the Received Signal Strength (RSS) model. This model views localization as a non-convex problem and employs an adaptive maximum likelihood estimation to minimize localization errors. An extensive simulation study is carried out to measure the performance of the intended approach in minimizing the localization error. The results unequivocally demonstrate that our localization scheme achieves higher accuracy in locating sensor nodes while reducing deployment costs. Comparative analysis against existing methods further underscores the significance of our approach.

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Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%

Enhancing Location Accuracy by Minimizing RMS Using RSS-AMLE in WSN

T P

2024

J. Infor. Electr. Electron. Eng.

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“…A few localization technique based on hybrid methodology strategy are also considered [24]. These strategies provide support for both the range free based and range based methodologies.…”

Section: Related Workmentioning

confidence: 99%

A Radio Signal Strength Based Localization Error Optimization Technique for Wireless Sensor Network

Thimmaiah¹,

Mahadevan²

2018

IJEECS

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Wireless Sensor Networks (WSN) is useful in collecting data from various sensor devices that are distributed over a network which is generally positioned in a stationary manner. Wireless sensor based communication system is an ever growing sector in the industry of communication. Wireless infrastructure is a network that enables correspondence between various devices associated through an infrastructure protocol. Finding the position or location of sensor node (Localization) is an important factor in sensor network for proving efficient service to end user. The existing technique proposed so for adopt AOA (Angle of Arrival), TOA (Time of Arrival) etc… suffers in estimating the likelihood of localization error and induces high cost of deployment. To cater this in this work the author proposes a cost effective RSS (Received signal strength) based localization technique and also proposes an adaptive information estimation to reduce or approximate the localization error in wireless sensor network. The author compares our proposed localization model with existing protocol and analyse its efficiency.

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“…In 2012, Liu et al [43] also proposed a hybrid of bounding box and DV-Hop, whereby, with fewer known nodes, the former scheme is applied and DV-Hop is applied in the latter case. In the same year, Chen and Zhang [44] combined traditional DV-Hop and PSO to correct the position estimated by two-dimensional hyperbolic localization.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Fuzzy Centroid with MDV-Hop BAT Localization Algorithms in Wireless Sensor Networks

So-In

Katekaew

2015

International Journal of Distributed Sensor Networks

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Many applications employing wireless sensor networks have been available in real-world scenarios. Their popularity is due to distinctive characteristics, for example, small scale, multisensing capability, and cost-effective deployment. However, there are constraints including routing, reliability, and especially localization, in particular without the aid of global positioning services, the lack of satellite coverage. In addition, if embedded, the overhead will be increased with hardware costs and shortened battery life. Thus, a range-free-based localization scheme is promising and is being pursued as a cost-effective approach. Centroid is one of the pioneer low complexity range-free estimation algorithms, and DV-Hop is another algorithm that has no requirements for distance information. However, their main drawbacks are location estimation precision. Recently, a soft-computing-based approach used to address uncertainty and approximation has been proposed as a low cost solution to gain precision, and, therefore, this research investigates its integration and then proposes a novel hybrid localization algorithm utilizing key characteristics of Centroid and DV-Hop. This hybrid scheme employs an extra weight with signal normalization derived from a fuzzy logic function in Centroid. The research also integrates a BAT algorithm of the modified DV-Hop. These combinations demonstrate the effectiveness in the simulation and location error reduction with time complexity trade-off.

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An Adaptive Hybrid Localization Algorithm for Wireless Sensor Network

Cited by 8 publications

References 3 publications

Enhancing Location Accuracy by Minimizing RMS Using RSS-AMLE in WSN

Enhancing Location Accuracy by Minimizing RMS Using RSS-AMLE in WSN

A Radio Signal Strength Based Localization Error Optimization Technique for Wireless Sensor Network

Hybrid Fuzzy Centroid with MDV-Hop BAT Localization Algorithms in Wireless Sensor Networks

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